LAUSR

Abstract In recent years, the number of stakeholders of construction projects has significantly increased; this has required the simultaneous achievement of competing objectives, such as reductions in the time, cost, resources, and environmental impact of a project, for example. In order to achieve a balance between these objectives, several multiple-objective construction scheduling models have been reported in the literature. However, several challenges have been encountered, due to the complexities of modelling and visualizing more than three objectives simultaneously. Some of these challenges are addressed in this work via the development of a many-objective scheduling model (MOSM) based on a non-dominated sorting genetic algorithm for the simultaneous optimization of four objectives: time, cost, resources and environmental impact. Coordinate plots are used to visualize the trade-offs made between all four of these objectives. A weighted sum is introduced that offers the project team the freedom to choose an optimal solution, depending on the specific priorities of the project, and the practical application of the model is demonstrated via a case study. Our MOSM allows the optimal outcome to be achieved in construction projects with multiple objectives.